Implementation of an Optimal First-Order Method for Strongly Convex Total Variation Regularization

We present a practical implementation of an optimal first-order method, due to Nesterov, for large-scale total variation regularization in tomographic reconstruction, image deblurring, etc. The algorithm applies to $\mu$-strongly convex objective functions with $L$-Lipschitz continuous gradient. In the framework of Nesterov both $\mu$ and $L$ are assumed known -- an assumption that is seldom satisfied in practice. We propose to incorporate mechanisms to estimate locally sufficient $\mu$ and $L$ during the iterations. The mechanisms also allow for the application to non-strongly convex functions. We discuss the iteration complexity of several first-order methods, including the proposed algorithm, and we use a 3D tomography problem to compare the performance of these methods. The results show that for ill-conditioned problems solved to high accuracy, the proposed method significantly outperforms state-of-the-art first-order methods, as also suggested by theoretical results.Comment: 23 pages, 4 figure

The AFLOW Fleet for Materials Discovery

The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data driven research. With the intent to accelerate the development and the deployment of new technologies, the AFLOW Fleet for computational materials design automates high-throughput first principles calculations, and provides tools for data verification and dissemination for a broad community of users. AFLOW incorporates different computational modules to robustly determine thermodynamic stability, electronic band structures, vibrational dispersions, thermo-mechanical properties and more. The AFLOW data repository is publicly accessible online at aflow.org, with more than 1.7 million materials entries and a panoply of queryable computed properties. Tools to programmatically search and process the data, as well as to perform online machine learning predictions, are also available.Comment: 14 pages, 8 figure

Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

This corrects the article DOI: 10.1038/sdata.2017.179

A Frameshift in CSF2RB Predominant Among Ashkenazi Jews Increases Risk for Crohn's Disease and Reduces Monocyte Signaling via GMCSF

BACKGROUND & AIMS: Crohn's disease (CD) has the highest prevalence in Ashkenazi Jewish populations. We sought to identify rare, CD-associated frameshift variants of high functional and statistical effects. METHODS: We performed exome-sequencing and array-based genotype analyses of 1477 Ashkenazi Jewish individuals with CD and 2614 Ashkenazi Jewish individuals without CD (controls). To validate our findings, we performed genotype analyses of an additional 1515 CD cases and 7052 controls for frameshift mutations in the colony stimulating factor 2 receptor beta common subunit gene (CSF2RB). Intestinal tissues and blood samples were collected from patients with CD; lamina propria leukocytes were isolated and expression of CSF2RB and GMCSF-responsive cells were defined by mass cytometry (CyTOF analysis). Variants of CSF2RB were transfected into HEK293 cells and expression and functions of gene products were compared. RESULTS: In the discovery cohort, we associated CD with a frameshift mutation in CSF2RB (P=8.52x10-4); the finding was validated in the replication cohort (combined P=3.42x10-6). Incubation of intestinal lamina propria leukocytes with GMCSF resulted in high levels of phosphorylation of STAT5 and lesser increases in phosphorylation of ERK and AKT. Cells co-transfected with full-length and mutant forms of CSF2RB had reduced pSTAT5 following stimulation with GMCSF, compared to cells transfected with control CSF2RB, indicating a dominant negative effect of the mutant gene. Monocytes from patients with CD who were heterozygous for the frameshift mutation (6% of CD cases analyzed) had reduced responses to GMCSF and markedly decreased activity of aldehyde dehydrogenase; activity of this enzyme has been associated with immune tolerance. CONCLUSIONS: In a genetic analysis of Ashkenazi Jewish individuals, we associated CD with a frameshift mutation in CSF2RB. Intestinal monocytes from carriers of this mutation had reduced responses to GMCSF, providing an additional mechanism for alterations to the innate immune response in individuals with CD

Functional variants in the LRRK2 gene confer shared effects on risk for Crohn's disease and Parkinson's disease

Crohn’s disease (CD), a form of inflammatory bowel disease, has a higher prevalence in Ashkenazi Jewish than in non-Jewish European populations. To define the role of nonsynonymous mutations, we performed exome sequencing of Ashkenazi Jewish patients with CD, followed by array-based genotyping and association analysis in 2066 CD cases and 3633 healthy controls. We detected association signals in the LRRK2 gene that conferred risk for CD (N2081D variant, P = 9.5 × 10−10) or protection from CD (N551K variant, tagging R1398H-associated haplotype, P = 3.3 × 10−8). These variants affected CD age of onset, disease location, LRRK2 activity, and autophagy. Bayesian network analysis of CD patient intestinal tissue further implicated LRRK2 in CD pathogenesis. Analysis of the extended LRRK2 locus in 24,570 CD cases, patients with Parkinson’s disease (PD), and healthy controls revealed extensive pleiotropy, with shared genetic effects between CD and PD in both Ashkenazi Jewish and non-Jewish cohorts. The LRRK2 N2081D CD risk allele is located in the same kinase domain as G2019S, a mutation that is the major genetic cause of familial and sporadic PD. Like the G2019S mutation, the N2081D variant was associated with increased kinase activity, whereas neither N551K nor R1398H variants on the protective haplotype altered kinase activity. We also confirmed that R1398H, but not N551K, increased guanosine triphosphate binding and hydrolyzing enzyme (GTPase) activity, thereby deactivating LRRK2. The presence of shared LRRK2 alleles in CD and PD provides refined insight into disease mechanisms and may have major implications for the treatment of these two seemingly unrelated diseases

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

Genetic variants associated with age-related episodic memory decline implicate distinct memory pathologies

BACKGROUND: Approximately 40% of people aged ≥ 65 experience memory loss, particularly in episodic memory. Identifying the genetic basis of episodic memory decline is crucial for uncovering its underlying causes. METHODS: We investigated common and rare genetic variants associated with episodic memory decline in 742 (632 for rare variants) Ashkenazi Jewish individuals (mean age 75) from the LonGenity study. All-atom molecular dynamics simulations were performed to uncover mechanistic insights underlying rare variants associated with episodic memory decline. RESULTS: In addition to the common polygenic risk of Alzheimer's disease, we identified and replicated rare variant associations in ITSN1 and CRHR2. Structural analyses revealed distinct memory pathologies mediated by interfacial rare coding variants such as impaired receptor activation of corticotropin releasing hormone and dysregulated L-serine synthesis. DISCUSSION: Our study uncovers novel risk loci for episodic memory decline. The identified underlying mechanisms point toward heterogenous memory pathologies mediated by rare coding variants. Highlights: We demonstrated the contribution of the common polygenic risk of Alzheimer's disease to episodic memory decline. We discovered and replicated two risk genes associated with episodic memory decline&nbsp;implicated by rare variants, were discovered and replicated. We demonstrated molecular mechanisms and potential novel memory pathologies underlying interfacial rare coding variants. Molecular dynamics simulations were performed to understand the downstream effects of risk rare coding variants

Cytosine Methylation Dysregulation in Neonates Following Intrauterine Growth Restriction

Perturbations of the intrauterine environment can affect fetal development during critical periods of plasticity, and can increase susceptibility to a number of age-related diseases (e.g., type 2 diabetes mellitus; T2DM), manifesting as late as decades later. We hypothesized that this biological memory is mediated by permanent alterations of the epigenome in stem cell populations, and focused our studies specifically on DNA methylation in CD34+ hematopoietic stem and progenitor cells from cord blood from neonates with intrauterine growth restriction (IUGR) and control subjects.Our epigenomic assays utilized a two-stage design involving genome-wide discovery followed by quantitative, single-locus validation. We found that changes in cytosine methylation occur in response to IUGR of moderate degree and involving a restricted number of loci. We also identify specific loci that are targeted for dysregulation of DNA methylation, in particular the hepatocyte nuclear factor 4alpha (HNF4A) gene, a well-known diabetes candidate gene not previously associated with growth restriction in utero, and other loci encoding HNF4A-interacting proteins.Our results give insights into the potential contribution of epigenomic dysregulation in mediating the long-term consequences of IUGR, and demonstrate the value of this approach to studies of the fetal origin of adult disease